Linkedin How to

This is a re-post

Linkedin: How to use it and My response to Your Fathers Tool

This is in response to a comment on a recruitment group that using Linkedin to recruit is dated. I disagree and strongly have responded why. If you are a jobseeker or a recruiter my sourcing response may help you with hints on how to use Linkedin beyond the post--that is if you read this:-).

Subject: In response to Linkedin: Your Fathers Tool
I'm happy to be using tools that reach a broad range of experience levels. How can a tool be dated if it works? I still belong to this group which is a yahoogroup--- I still use organizations, associations, meetups and occassionally job board hunting, especially with earlier listservs that would date me but I still land quality candidates.

As a recruiter, I use anything that works to find quality talent and that could mean using a resource like Linkedin not for the talent that is visible but for the link to that talent. I use Linkedin similar to employee referral tools-- connecting with others that can connect you to the talent. I also respond to talent and recruiters to help them connect to each other. I don't get paid to do it I think its what makes me a great networker--I want to assist folks, and learn about matches or talent I might never have known about if I kept only within my circle.

Shame on any recruiter that doesn't use the tools that have proven impact to source. I challenge anyone without the means for fancy costly job boards where they can get direct access better to qualified networks of candidates than Linkedin. It is dependant on how you use it-- your technique for uncovering more talent through visible talent is what sets a great recruiter apart from the average. Track your results and you'll find that jobboards still deliver candidates, Linkedin delivers candidates, direct source delivers, employee referrals delivers talent..... Bottom Line know what works and don't stop at just one resource.

A note on Linkedin as a recruiting tool and as an agent for networking. When Linkedin started only marketing folks were using it, and a few recruiters got into the mix. Linkedin became what it is today as a Job Connection resource because of those recruiters using it as a channel to reach out to folks otherwise not advertised. Ask how someone heard about Linkedin-- it is usually through recruiter or school. Prior to Linkedin charging for JobPosts it was one more low cost networking tool or source to get the word out that companies were hiring. Like List and Groups before Linkedin it will continue to be used by our profession.

It is up to the employment profession to think creatively to reach the market and talent they need through any and all resources possible. If you limit your tools to a demographic group-- you are limiting your ability to source a whole pot of exceptional talent. Likewise its up to us to keep abreast of new tools-- I try them all, but I track what is successful.
Oh by the way if you aren't a fan of Linkedin Talent--- just send over all

your contact info v-card downloaded to me, and I'm sure we all would be happy to network with those folks;-)



Sue

Susan Hand in Boston
http://twitter.com/SusanHand

Data Scientist

Data Scientist

Location: Burlington, MA

I am seeking a Data Scientist to join our Nokia Big Data Analytics team in Burlington, MA. We are seeking top talent to analyze and act on petabytes of data to provide highly relevant experiences to consumers.

The Team: The Big Data Analytics team works on the cutting edge of a breadth of products, research, customers and technologies. Missioned to improve, tests, analyze, define and shape data driven solutions – it affords the individual a breadth of possibilities in a supportive dynamic team.

The Cool Role:
This role is a key contributor to the Nokia team and Partners. Imagine the breadth of exposure to cutting edge data and the impact on the future. Day to Day this role will develop statistical models for data generated by a breadth of data-driven applications and products. Think Big Data and imagine working on cutting edge information from gathering to throughput; Performing data mining and machine learning tasks such as classification, prediction and clustering; Evaluating, Designing, improving and testing predictive and other statistical models. The successful candidate will be able to assimilate data and build analytics applications, including dashboards and tools for exploratory data visualization and analysis. Communicating results and presenting to all levels of organization of including peers, senior management and internal customers is necessary

Qualifications/Requirements:

• Bachelor’s Degree is required (MS and PhD preferred)
• 5 + years of experience applying a broad range of statistical concepts and methods, including predictive techniques from data source
• 5+ years of Programming success with R OR Python OR Matlab (Java is a plus)
• Insight and ability to recognize, derive, design, develop and analyze data from conception to output
• Proven ability and flexibility coupled with knowledge and speed in pattern recognition, and responding by creating and implementing structure
• Excellent Communication Skills (including but not limited to Presentation and reasoning skills)
• Curiosity and Passion for Data with the ability and drive for results
• Excellence and working knowledge in analytical and algorithm design  

Preferred or Nice to Haves

• Previous experience with unstructured or semi structured Data is preferred
• Previous success in Machine learning data mining, natural language, or info retrieval is a plus
• PHD or MS in Mathematics, Statistics, and CS preferred
• Preferred Java programming is a plus.
• Experience with visualization tools based on JavaScript is a plus
• Experience with relational databases (SQL) and big data platform (e.g., Hadoop) is a plus.
• Innovative, proactive and think outside the box  

 Send resumes to ext-susan.hand@nokia.com